2026-03-28 22:01:57
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Today at a glance:
📦 PDD: Growth Pivot
📱 Xiaomi: Memory Crunch
🛵 Meituan: The Subsidy War
🛳️ Carnival: Energy Volatility
🐶 Chewy: Loyalty Flywheel
Temu parent PDD Holdings capped off FY25 with Q4 revenue rising grew 12% Y/Y to $17.7 billion ($0.4 billion miss), an acceleration from the single-digit growth seen earlier in the year.
The core story is Temu’s stabilization. After struggling with the end of the US de minimis tax exemption, the global bargain app regained momentum during the holiday season and now operates in nearly 100 markets. Transaction services revenue (which includes Temu) surged 19% to $9.1 billion in Q4, suggesting that PDD is successfully navigating the new tariff landscape by diversifying into Europe and optimizing its supply chain.
While growth improved, net income slid 11% to $3.5 billion ($0.52 EPADS miss). The company continued its aggressive campaign of “deliberate sacrifice” to fortify its ecosystem. Margins compress slightly for another quarter.
Management has launched a massive three-year strategy aimed at “building another Pinduoduo” by shifting focus from raw traffic to deep supply-chain integration.
Support program: PDD is pouring resources into merchant support and last-mile logistics, including a new “free delivery to villages” pilot that establishes warehouses in remote rural areas to unlock untapped consumption.
Regulatory headwinds: The quarter was not without friction. Beijing authorities deepened their probe into PDD’s accounting and tax practices following a highly publicized literal fistfight between employees and regulators in December.
Supply chain conviction: Co-CEO Jiazhen Zhao emphasized that 2026 marks a new decade for the firm, with an “all-in” mindset on supply chain investment that will continue to pressure short-term margins.
Despite the earnings miss, the stock jumped post-earnings as investors cheered the revenue acceleration and easing trade tensions. The US Supreme Court’s recent ruling against certain 2025 tariffs and the potential creation of a “US-China Board of Trade” have provided a much-needed reprieve for cross-border e-commerce.
PDD’s balance sheet remains a fortress, with cash and short-term investments climbing to ~$60 billion. Management continues to warn that quarterly profits will fluctuate as they prioritize merchant retention over short-term earnings.
2026-03-27 20:03:56
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This week, Anthropic launched a research preview that allows Claude Code and Cowork to take direct control of your computer—pointing, clicking, and typing like a human operator. Through a new feature called Dispatch, users can assign a complex task from their phone and return later to a finished deliverable on their desktop.
It follows the recent hype around OpenClaw, whose founder, Peter Steinberg, just joined OpenAI. Steinberg’s move is a clear signal that OpenAI is preparing its own response. It’s the latest display of the intensifying AI agent race. While Anthropic is doubling down on autonomous work, others can no longer afford to fall behind.
Today at a glance:
🤖 OpenAI: The End of Side Quests
🏭 Terafab: The Silicon Bottleneck
📱 Apple: Maps Turn Into Ad Space
OpenAI spent the last two years acting like it could build everything at once: the chatbot, the coding assistant, the browser, the shopping layer, the hardware device, and even a video-generation app aimed at creators and studios. That made the company look unstoppable, but also increasingly spread out.
Anthropic has been gaining ground with developers and enterprise users, especially in coding. Meanwhile, OpenAI has been juggling a growing list of products competing for the same talent, attention, and compute. Consumer experiments may generate buzz, but they do little to help if the company is heading toward an IPO and needs to show a clear path to profitability.
In recent weeks, OpenAI made clear that the era of endless experimentation may be fading. Leadership is reportedly pushing the company away from distracting side quests and back toward coding and enterprise productivity.
Here’s what that looks like in practice:
Sora App shuttered: Just six months after its splashy standalone launch, OpenAI is closing the Sora app. Despite hyper-realistic results, the resource-intensive nature of video generation has made it an early casualty of the new lean strategy.
$1 billion Disney deal collapses: The partnership, which intended to bring Disney characters into the Sora ecosystem, was officially terminated this week. It is a stark admission that the Hollywood dream is being deprioritized in favor of more stable revenue streams.
Desktop super app: Rather than maintaining fragmented products like the Atlas browser and Codex coding tool, OpenAI is folding them into a single unified desktop interface. The goal is to stop users from context-switching.
Transaction retreat: OpenAI is stepping back from owning the payment flow inside ChatGPT. Instead of handling purchases directly, it is repositioning as a product discovery and referral layer, offloading the operational complexity of e-commerce to retailers.
ChatGPT’s success has made OpenAI, as Ben Thompson put it, an accidental consumer tech company. Altman & Co. then tried to build ten startups under one roof. Now OpenAI is being forced to act less like a playground for new ideas and more like a business with a clearer center of gravity.
While apps like Sora were flashy and viral, video generation is expensive, difficult to moderate, and full of copyright landmines. When you are preparing for a possible IPO, these are the kinds of projects that get scrutinized fast. Viral clips of dogs driving cars don’t carry the same weight as high-margin enterprise seats.
That pressure is showing up most clearly in enterprise. Anthropic’s momentum with Claude Code and its $2.5 billion revenue run-rate has made the battle for workplace adoption much more urgent. OpenAI seems to have decided that the biggest prize is becoming the default software layer for work, and that changes how it thinks about resources. Every GPU spent on a side quest is one not being used to win the high-stakes battle for the developer’s desktop.
Instead of chasing every adjacent opportunity, the company now seems to be asking a simpler question: Does this help us win coding and enterprise? If the answer is no, it becomes much easier to cut, even if the project is flashy and has big-name partners attached.
For years, frontier AI companies were rewarded for launching whatever felt like a big idea. This next phase is less about proving how many cool things you can launch and more about proving you know which ones are actually worth building. OpenAI is starting to act less like an AI theme park and more like a company picking its battles. Sam Altman has already proven he is exceptional at fundraising and dealmaking. Now comes the hard part. OpenAI has to prove it can be exceptional at generating cash.
Elon Musk’s newest big idea is not a rocket or a robotaxi. It’s a chip factory. This week, Musk unveiled Terafab, a chip-manufacturing joint venture between Tesla, SpaceX, and xAI that early reports peg at ~$25 billion.
The project aims to supply the specialized compute needed for self-driving cars, humanoid robots, and a newly revealed “Orbital Data Center” system. Musk’s vision is split into two distinct lines: the AI5/AI6 series for terrestrial robotics and the D3 series, which are high-power chips hardened for the hostile environment of space.
Terafab matters because it exposes a growing reality at the center of the AI boom. The Big Three foundries (TSMC, Samsung, and Intel) cannot expand quickly enough to meet Musk’s exponential projections. As Musk bluntly put it:
“We either build the Terafab or we don’t have the chips.”
The scale is almost incomprehensible. Musk suggested Terafab will eventually span 100 million square feet—roughly 10x the size of Giga Texas—requiring over 10 gigawatts of power. Musk says bringing fabrication, memory, and packaging under one roof in Austin could create a ‘recursive design loop,’ allowing chips to be designed, printed, and tested in days rather than months. If successful, it would give Musk’s companies far more control over the chip-development cycle.
Here is what stands out from a business perspective:
The ambition is enormous: Terafab targets 1 Terawatt of annual compute. For context, analysts have argued that ambition is on the order of current relevant global semiconductor capacity.
Pivot to space-first compute: In a surprising twist, Musk says roughly 80% of Terafab’s output would eventually be dedicated to space-based AI satellites. He argues that solar irradiance is 5x stronger in orbit, potentially making space-based inference cheaper than terrestrial data centers within three years.
The xAI link-up: Terafab shows how closely xAI is becoming tied to Musk’s broader industrial ecosystem. That may strengthen the strategic logic, but it also raises fresh questions about how the spending is divided across Tesla, SpaceX, and xAI.
The cost question is unavoidable. Building a 2nm-capable fab from scratch is one of the most capital-intensive bets in industrial history. Even before reaching full scale, Terafab will pressure capital budgets that are already stretched thin.
Tesla is the most vulnerable link here. Its decline in vehicle sales and margin compression leave little room for error. While it generated $6.2 billion in Free Cash Flow in 2025, Goldman Sachs estimates that figure could turn negative in 2026.
SpaceX is currently the bank for this vision, with a potential $750 billion IPO on the horizon to fund these orbital ambitions. Skepticism remains high because chip manufacturing has moved toward specialization for a reason. NVIDIA designs, TSMC manufactures, and ASML provides the tools. By trying to pull the entire stack under one roof, Musk is betting that vertical integration can overcome decades of specialized industry expertise.
Still, Musk may be right about the broader bottleneck. If Tesla wants 10 billion Optimus robots by 2040 and SpaceX wants a million AI satellites, then chip supply stops being a procurement issue and starts becoming a fundamental constraint on the entire vision. Musk has made vertical integration look visionary before, but Terafab is a reminder that the ultimate bottleneck is the balance sheet.
Apple just found a new place to sell ads.
This week, the company announced Apple Business, a free all-in-one platform that bundles device management, corporate mail, and brand tools. The company removed the monthly subscription fees previously required for these management tools.
In other words, Apple is lowering the barrier for millions of small businesses to formalize their digital presence. This free offering functions as a customer acquisition tool for Apple's newest high-margin revenue stream: Ads are coming to Maps.
Starting this summer in the US and Canada, businesses will be able to buy priority placement at the top of Maps search results and inside a new Suggested Places feed. It is a direct page from the Google Maps playbook, launched nearly 13 years later.
The shift toward advertising is a necessity for Apple’s valuation.
Apple still makes the bulk of its revenue from Products. But Services generated $86 billion in gross profit over the last 12 months (LTM). That’s good for 42% of Apple’s overall gross profit. The gap between Products and Services is narrowing rapidly. The two lines below will eventually cross. It’s a matter of when, not if.
Apple’s Services division now operates at a 77% gross margin—nearly double the margin of the Products segment. Every dollar of local ad revenue Apple generates from a coffee shop or retailer is almost pure profit, helping insulate the bottom line as hardware upgrade cycles lengthen.
This ad push also serves as a hedge against regulatory headwinds.
For years, a massive chunk of Apple’s Services profit came from a single source: the multi-billion dollar check Google pays to be the default search engine on Safari. Analysts now estimate this payment has ballooned to $28 billion annually.
The latest antitrust rulings in late 2025 and early 2026 did not ban these payments, but they did deliver a structural wake-up call. The courts stripped away Google’s ability to demand exclusivity, meaning Apple is now legally free to promote rivals alongside Google. More importantly, the ruling forces these contracts to be renegotiated every 12 months.
For Apple, the DOJ's message was clear: you can keep the money for now, but you can no longer outsource your search destiny to a single partner. By building its own search ad ecosystem inside Maps, Apple is essentially insourcing its revenue. They are moving from renting their search traffic to Google to owning the search intent themselves.
Apple is selling local intent. Unlike an App Store search, a Maps search happens at the very end of the purchase funnel. By turning Maps into a high-margin ad platform, Apple is showing that some of its most valuable economics come not from the glass and aluminum in your pocket, but from the data on where you’re going next.
That's it for today.
Happy investing!
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Disclosure: I own AAPL, GOOG, META, NVDA, and TSLA in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-03-24 20:05:20
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Robotaxis were supposed to threaten Uber.
Instead, Uber is trying to become the platform they run through.
In just a few weeks, the company has announced a flurry of partnerships across the autonomy stack — from software providers to fleet operators to vehicle manufacturers. NVIDIA. Zoox. Wayve. Motional. And the list keeps growing.
With nearly $10 billion in Free Cash Flow in 2025 alone, Uber now has the firepower to shape the future of autonomy.
The latest move came last week: a $1.25 billion investment in Amazon-backed Rivian to deploy up to 50,000 fully autonomous robotaxis by 2030.
At first glance, it looks like Uber is simply hedging its bets. But the strategy is now abundantly clear. Uber doesn’t want to build the best self-driving technology. It wants to own the marketplace around it.
And the economics behind that strategy tell a much bigger story.
Today at a glance:
🚖 Not just Rivian
🧠 Uber’s new playbook
⚖️ The hybrid advantage
📊 Who really wins here
2026-03-21 22:02:45
Welcome to the Saturday PRO edition of How They Make Money.
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📊 Monthly reports: 200+ companies visualized.
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📚 Access to our archive: Hundreds of business breakdowns.
📩 Saturday PRO reports: Timely insights on the latest earnings.
Today at a glance:
🇨🇳 Alibaba: $100 Billion AI Bet
🌐 Accenture: AI Transition Continues
🚚 FedEx: Efficiency Over Expansion
🍪 General Mills: Reinvestment Pains
🫒 Darden: Strategic Shifts
🚖 Didi: Cost of Conquest
🧘🏻 Lululemon: Global Tug-of-War
✍️ DocuSign: Billings Hit $1 Billion
🏥 HealthEquity: Asset & Margin Records
🌎 dLocal: $1 Billion Milestone
Alibaba’s Q3 FY26 (December quarter) saw revenue rise 2% Y/Y to $40.7 billion ($1.4 billion miss), though like-for-like growth (excluding exited businesses like Sun Art and Intime) was a more robust 9%.
The headline story was a 67% plunge in adjusted net income, as the company doubled down on its investment phase. This aggressive spending centers on three areas: quick-commerce subsidies, user experience, and a massive build-out of AI infrastructure.
The company is effectively cannibalizing short-term retail profits to fund a full-stack AI future:
Cloud Intelligence Group: Revenue growth accelerated to 36% Y/Y, with AI-related product revenue posting its tenth consecutive quarter of triple-digit growth. CEO Eddie Wu set a bold new target to reach $100 billion in annual Cloud and AI revenue within five years. To accelerate monetization, Alibaba recently hiked prices for cloud and storage services by up to 34%.
T-Head & Token Hub: Alibaba is vertically integrating its AI via its proprietary chip unit, T-Head, which has now shipped over 470,000 AI chips. The newly formed Alibaba Token Hub (ATH) group consolidates all AI units under Eddie Wu to streamline the adoption of “Model-as-a-Service” (MaaS).
China E-commerce & Quick Commerce: While core e-commerce revenue grew 6%, the Quick Commerce segment surged 56% to ~$3 billion. This business is currently a loss leader used to defend market share against Meituan and JD.com, with a goal of hitting RMB 1 trillion in Gross Merchandise Value (~$143 billion) by FY28.
The quarter included significant headwinds. The surprise departure of Junyang Lin, a lead Qwen developer, raised questions about research continuity. In addition, while the Qwen App surpassed 300 million MAUs, the rise of agentic AI has given Tencent’s Weixin/WeChat ecosystem an early advantage.
Alibaba’s management characterized the current profit dip as a deliberate choice. They project that the Quick Commerce segment will turn profitable by FY29 and that the integration of T-Head chips will enable “non-linear leaps” in cloud profitability by reducing reliance on expensive external silicon.
2026-03-20 20:03:57
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Capital is shifting aggressively toward chips, data centers, and model infrastructure. At the same time, management teams are openly questioning how much human labor their future operations actually require.
ServiceNow CEO Bill McDermott recently warned that AI agents could push unemployment for new college graduates into the mid-30% range within two years. While that prediction sounds extreme, the broader shift is already manifesting in corporate behavior.
This week offered three very different examples of that shift.
Today at a glance:
🤖 Meta: More Chips Fewer Humans
📱 Tencent: Agents Meet Distribution
☁️ Micron: Demand Goes Vertical
Meta’s massive AI CapEx ramp continues to materialize, one infrastructure deal after another.
This week, the company signed a deal worth up to $27 billion over five years with AI cloud provider Nebius, including $12 billion of dedicated capacity starting in early 2027. It is another reminder that Zuck is racing to lock in as much compute as possible before capacity tightens further.
At the same time, Reuters reported that Meta is considering layoffs that could affect 20% or more of its workforce, though the company pushed back, calling the report speculative. If it happens, it would be Meta’s biggest cut since the ‘year of efficiency’ layoffs in 2023.
The two headlines are connected. Meta is not slowing its AI spending. It is reallocating. The company wants more data centers, more chips, and fewer workers doing jobs that AI can increasingly automate. Reuters noted that analysts estimate cuts of that size could save roughly $6 billion. That barely moves the needle for a company planning ~$125 billion in 2026 CapEx.
The bigger picture is that Meta is starting to look like the clearest example of what the AI era may do to Big Tech cost structures. The new org chart may be built less around adding headcount and more around adding compute.
Tencent’s core business is strong enough to fund a much more aggressive AI push. Q4 revenue rose 13% Y/Y to RMB 194 billion (~$28 billion), while net profit climbed 15%, helped by the higher-margin mix shift toward gaming and advertising.
Gaming led the quarter: Overseas gaming revenue surged 32% to RMB 21.1 billion in Q4. Success was driven by Supercell’s recovery (notably Clash Royale) and the breakout hit Delta Force. Meanwhile, China gaming revenue grew 15% to RMB 38.2 billion, supported by evergreen titles and the launch of Valorant Mobile.
Ad tech is scaling efficiently: Marketing services rose 17% to RMB 41.1 billion. Tencent said its AiM Plus ad model uses generative AI to create and target content, helping the business outgrow the broader Chinese advertising market.
Tencent’s previously measured AI posture is giving way to a much more aggressive one. The company now plans to double AI investment to over RMB 36 billion in 2026 (~$5 billion), funded in part by reduced share buybacks. That push also includes a major Hunyuan 3.0 upgrade expected in April, backed by a restructured research team.
Agents inside the super app: Tencent is moving beyond chatbots to agentic AI. It recently launched QClaw (an AI assistant integrated into WeChat) and WorkBuddy, leveraging the viral OpenClaw framework to automate tasks like travel booking and ride-hailing for its 1.42 billion MAUs.
Cloud is becoming a profit engine: Business Services generated a record RMB 5 billion in adjusted operating profit for the year, showing that Tencent’s pivot toward higher-quality PaaS and SaaS is working.
GPU supply constraints held back hardware purchases in Q4, but Tencent expects that to change in 2026 as H200 chips become more available. The bigger takeaway is that Tencent now has the cash flow, distribution, and product surface area to turn AI from an experiment into a real platform advantage.
Micron just released its Q2 FY26 earnings (February quarter), and the results suggest this cycle is accelerating faster than even bullish investors expected. While the stock dipped on aggressive spending plans, the underlying fundamentals remain extraordinary.
Revenue for Q2 skyrocketed 196% Y/Y to $23.9 billion, beating consensus by over $4.5 billion. To put that in perspective, Micron’s revenue guidance for the next quarter alone (~$33.5 billion) now exceeds the full-year revenue of every year in the company’s history through 2024.
Gross margins hit 74%, up from 56% just three months ago. Micron’s guidance for the next quarter points to an 81% gross margin, a figure that actually edges out NVIDIA’s current levels.
So, why did the stock slide? The answer lies in the massive capital requirements to stay on top.
CapEx surge: Micron raised its FY26 CapEx forecast to over $25 billion, up from the $20 billion discussed last quarter.
2027 ramp: Management warned that fiscal 2027 spending will “step up meaningfully,” increasing by more than $10 billion over 2026 levels.
The investor dilemma: Revenue is booming, but some investors are uneasy about how much cash Micron must pour into fabs in Idaho and New York to keep up.
The memory shortage has evolved beyond an AI-only narrative. It is now rippling through the broader electronics ecosystem.
HBM4 momentum: Micron has begun volume shipments of HBM4 for NVIDIA’s next-generation platforms, securing its position in a market many feared it would lose to SK Hynix and Samsung.
A longer shortage? While analysts once hoped supply would normalize by 2027, some industry leaders now think tightness could persist for four to five more years.
Consumer spillover: HP recently said memory prices roughly doubled in a single quarter. As Micron prioritizes high-margin AI memory, standard PC and phone manufacturers are fighting for scraps, driving hardware costs higher for everyone.
NVIDIA’s Vera Rubin allocation: The next major catalyst is the volume of HBM4 orders for NVIDIA’s upcoming Vera Rubin line. Any shift in how NVIDIA allocates these orders between the Big Three (Micron, Samsung, SK Hynix) will move the needle significantly.
Margin ceiling: With gross margin guidance at 81%, the market will be watching to see whether Micron is nearing a ceiling for profitability or whether pricing power can push margins even higher.
For now, Micron is one of the primary beneficiaries of AI’s second-order effects. Training and inference need compute, compute needs memory, and the world still cannot build enough of it. The open question is no longer whether the demand is real, but how long supply can remain this far behind it.
That's it for today.
Happy investing!
Thanks to Fiscal.ai for being our official data partner. Create your own charts and pull key metrics from 50,000+ companies directly on Fiscal.ai. Save 15% with this link.
Disclosure: I own META and TCEHY in App Economy Portfolio. I share my ratings (BUY, SELL, or HOLD) with App Economy Portfolio members.
Author's Note (Bertrand here 👋🏼): The views and opinions expressed in this newsletter are solely my own and should not be considered financial advice or any other organization's views.
2026-03-17 20:03:12
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“The inference inflection has arrived.”
That was Jensen Huang’s message at NVIDIA’s annual GTC keynote on Monday.
The company came into the event with something to prove. NVIDIA is already worth more than $4.4 trillion, but the stock had been under pressure this year as investors looked for evidence that the AI boom was still expanding. Huang’s answer? NVIDIA now sees at least $1 trillion of AI chip revenue opportunity through 2027.
But that number comes with an important catch.
This is not a new annual revenue guide. It is a cumulative platform forecast extending the old $500 billion through 2026 outlook by one more year. In other words, the message from GTC was less about a sudden new explosion in near-term sales and more about something arguably more important. NVIDIA is trying to prove that the next phase of the AI race will be defined by inference, agentic workloads, and the full AI factory. And the company intends to own all three.
Let’s cover in plain English the four key takeaways and what they imply for NVIDIA’s outlook, the broader AI trade, and the public companies tied to it.
Today at a glance:
A trillion-dollar outlook with a catch
Inference is the new battlefield
The moat moves up the stack
Winners and losers from GTC